Internet advertising is ubiquitous. Web advertising can be targeted to a person viewing information on various client devices (e.g., while “browsing” online using a desktop computer or mobile device). When a user visits a web page, the client device presenting the web page (e.g., using a browser application) and the web server and other data servers providing the web page content interact to identify the user. In some situations, a client device and other servers interact further to identify various interests, characteristics, or attributes of the user. For example, a user might visit a web page of a travel site, and an online advertiser might want to know not only information regarding the occurrence of such a visit, but also might also want to know certain characteristics of the user behavior or interest as expressed during the visit.
Based on the demographics of the user—such as if the user is within some age range (e.g., age 24-36) and/or gender, and/or has an annual income within some particular annual income range (e.g., $50 k-$75 k, $75 k-$100 k, etc.)—the advertiser might present a particular advertisement or message on the web page. In some cases the advertiser might want to select a particular advertisement based on a particular demographic; for example, if the user is identified as having an annual income greater than $100 k, then the advertiser might present an advertisement for luxury vacation packages. If the user is identified as having an annual income less than $100 k then the advertiser might want to present an advertisement for budget vacation packages.
In some cases, the demographics pertaining to specific users are stored at a server, or at multiple servers, depending on the scale of the data provider. Such a demographic storage technique is effective to screen a user vis-à-vis attributes that are relatively unchanging and/or are readily captured in standard attribute taxonomies. However, in some cases, an Internet advertiser might want to know the specific site (e.g., the URL of a particular travel site) that the user is currently visiting, and further, the advertiser might want to consider information derived from the particular web page the user is visiting (e.g., “Caribbean travel destinations”, “July 23 departure date”, etc.) in order to target that user with an even more relevant advertisement or message. Legacy techniques can look up certain demographics (e.g., from a database or at a server) pertaining to a particular user, however legacy techniques fail to capture specific user interaction with web page components at the web page that the user is currently browsing. Techniques are needed to address the problem of presenting targeted advertisements to a targeted online user based on instantaneous user interests (e.g., based on capture of real-time user behaviors) that are determined from user interaction with web page components.
None of the aforementioned legacy approaches achieve the capabilities of the herein-disclosed techniques for evaluating page content to determine user interest. Therefore, there is a need for improvements.